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The impact of forest architecture parameterization on GPP simulations

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Abstract

The presence of a forest strongly affects ecosystem fluxes by acting as a source or sink of mass and energy. The objective of this study was to investigate the influence of the vertical forest heterogeneity parameterization on gross primary production (GPP) simulations. To introduce a heterogeneity effect, a new method for the upscaling of the leaf level GPP is proposed. This upscaling method is based on the relationship between the leaf area index (LAI) and the leaf area density (LAD) profiles and the standard sun/shade leaf separation method. The effect of the crown shape and foliage distribution parameterization on the simulated GPP is confirmed in a comparison study between the proposed method and the standard sun/shade upscaling method. The observed values used in the comparison study are assimilated during the vegetation period on three distinguished forest eddy-covariance (EC) measurement sites chosen for the diversity of their morphological characteristics. The obtained results show (a) the sensitivity of the simulated GPP to the leaf area density profile, (b) the capability of the proposed scaling method to calculate the contribution of the different canopy layers to the entire canopy GPP, and (c) a better agreement with the observations of the simulated GPP with the proposed upscaling method compared with the standard sun/shade method.

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Acknowledgments

The research work described in this paper was realized as a part of the project “Studying climate change and its influence on the environment: impacts, adaptation, and mitigation” (43007) financed by the Ministry of Education and Science of the Republic of Serbia within the framework of integrated and interdisciplinary research for the period 2011–2014.

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Authors and Affiliations

  1. Faculty of Sciences, Department of Physics, University of Novi Sad, Dositej Obradovic Sq. 4, Novi Sad, 21000, Serbia

    Ana Firanj & Zorica Podrascanin

  2. Faculty of Agriculture, Department for Field and Vegetable Crops, University of Novi Sad, Dositej Obradovic Sq. 8, Novi Sad, 21000, Serbia

    Branislava Lalic

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  1. Ana Firanj
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  2. Branislava Lalic
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Correspondence to Ana Firanj.

Appendix A

Appendix A

1.1 Flux partitioning in LAPS

  1. 1.

    Fluxes from the leaf level to the canopy air space are represented in the following equations:

    $$ {H}_c=\rho {c}_p\frac{2\left({T}_c-{T}_a\right)}{r_b}, $$
    (A.1)
    $$ \lambda {E}_c=\left({e}_{*}\left({T}_c\right)-{e}_a\right)\frac{\rho {c}_p}{\gamma}\left(\frac{W_c}{r_b}+\frac{1-{W}_c}{r_b+{r}_c}\right), $$
    (A.2)

    where c refers to the canopy, and the other values are ρ, air density (kg m−3); C p , specific heat of the air at constant pressure (J kg−1 K−1); γ, the psychrometric constant (hPa K−1); T c , leaf temperature (K); T a , temperature of the canopy air space (K); r b bulk canopy boundary layer resistance (s m−1); and r c is the bulk canopy stomatal resistance (s m−1); e * (T c ) saturated vapor pressure for the canopy temperature (hPa); e a , vapor pressure inside the canopy air space (hPa); W c , part of the vegetation wet surface; and λ is the latent heat of evaporation.

  2. 2.

    Fluxes from the ground to the canopy air space are represented in the following equations:

    $$ {H}_{gs}=\rho {c}_p\frac{2\left({T}_{gs}-{T}_a\right)}{r_d}, $$
    (A.3)
    $$ \lambda {E}_{gs}=\frac{\left({\alpha}_s{e}_{*}\left({T}_{gs}\right)-{e}_a\right)}{r_b+{r}_d}\frac{\rho {c}_p}{\gamma}, $$
    (A.4)

    where gs refers to the ground surface; the other values are T gs , ground surface temperature; e * (T gs ), saturated vapor pressure for the ground surface temperature; r d is the aerodynamic resistance between the soil surface and the canopy air space (s m−1); and α s is the soil wetness factor (Mihailovic et al. 1995).

  3. 3.

    Fluxes from the canopy air space to the reference level above vegetation are represented in the following equations:

    $$ {H}_r={H}_c+{H}_{gs}=\rho {c}_p\frac{\left({T}_a-{T}_r\right)}{r_a}, $$
    (A.5)
    $$ \lambda {E}_r=\lambda {E}_c+\lambda {E}_{gs}=\frac{\rho {c}_p}{\gamma}\frac{\left({e}_a-{e}_r\right)}{r_a}, $$
    (A.6)

    where r is the reference level; the other values are T r , air temperature at the reference level; e r , vapor pressure at the reference level above the vegetation; and r a is the aerodynamic resistance (s m−1).

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Firanj, A., Lalic, B. & Podrascanin, Z. The impact of forest architecture parameterization on GPP simulations. Theor Appl Climatol 121, 529–544 (2015). https://doi.org/10.1007/s00704-014-1251-7

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